Disentangling the influence of hydroclimatic patterns and agricultural management on river nitrate dynamics from sub-hourly to decadal time scales

Highlights

• Analysis of river nitrate dynamics from infra-hourly to decadal time scales

• Storm event concentration-discharge patterns vary seasonally

• Long-term nitrate trends are influenced by weather and climate patterns.

• Catchment changed from chemodynamic to more chemostatic behaviour

Abstract

Despite extensive efforts to reduce nitrate transfer in agricultural areas, limited response is often observed in the nitrate concentration in rivers. To investigate the reasons for this limited response, nitrate dynamics in a 100 km² agricultural catchment in eastern Germany was analysed from sub-hourly to decadal time-scales. Sub-hourly analysis of storm event dynamics during a typical hydrological year (2005–2006) was performed to identify periods of the year with high leaching risk and to link the latter to agricultural management practices in the catchment. Dynamic Harmonic Regression analysis of a 32-year (1982–2014) record of nitrate and discharge revealed that i) the long-term trend in nitrate concentration was closely related to that in discharge, suggesting that large-scale weather and climate patterns were masking the effect of improved nitrogen management on nitrate trends; ii) a persistent seasonal pattern with winter concentration maxima and summer minima could be observed, which was interpreted in terms of a dynamic nitrate concentration profile in the soil and subsoil; and iii) the catchment progressively changed from chemodynamic to more chemostatic behaviour over the three decades of study, which is a sign of long-term homogenisation of nitrate concentrations distribution over depth. This study shows that detailed physical understanding of nitrate dynamics across time scales can be obtained only through combined analysis of long-term records and high-resolution sensor data. Hence, a joint effort is advocated between environmental authorities, who usually perform long-term monitoring, and scientific programmes, which usually perform high-resolution monitoring.

Introduction

Production of synthetic nitrogen (N) fertilisers through the Haber-Bosch process and their application to arable fields have significantly contributed to increased food production worldwide (Galloway et al., 2004). However, they have also increased the amount of reactive N in the environment, which can subsequently have adverse effects on terrestrial and aquatic ecosystems, the Earth's climate and human health (Galloway et al., 2003, Sutton et al., 2011, Vitousek et al., 1997). Most N emissions in water in Western countries come from diffuse agricultural sources (Bouraoui and Grizzetti, 2011, Dupas et al., 2013) and nitrate is the dominant form transferred in intensively farmed areas (Mellander et al., 2012, Molenat et al., 2008, Rodriguez-Blanco et al., 2015).

National, federal or international regulations have been set up worldwide to reduce nitrate-N transfer to water. In the European Union, the Nitrate Directive (CEC 1991) and the Water Framework Directive (CEC 2000) provide guidelines for member states for national programmes of measures and evaluation protocols. Evaluation of long-term changes in nutrient concentrations in European rivers has highlighted little improvement in nitrate-N concentrations, despite implementation of the Nitrate Directive (Bouraoui and Grizzetti, 2011). One reason for this limited response to mitigation measures is the time lag due to the multi-year transfer time of nitrate-N in the unsaturated and saturated zones of catchments (Fovet et al., 2015, Howden et al., 2010, Melland et al., 2012, Windolf et al., 2012, Worrall et al., 2009, Wriedt and Rode, 2006). To assess the effectiveness of mitigation measures, long-term water quality records are thus necessary (Bouraoui and Grizzetti, 2011), firstly because of this time lag, and secondly because catchments are influenced by large-scale weather and climate patterns which can affect river nitrate-N concentrations (Gascuel-Odoux et al., 2010). If not evaluated properly, the effect of adaptive agricultural management may be confounded by the effect of multi-annual weather patterns. In addition, the dynamics of stream chemistry are typically non-linear and non-self-averaging over existing observation time lengths (Aubert et al., 2014, Kirchner and Neal, 2013); thus, non-stationary techniques such as Dynamic Harmonic Regression (DHR) are necessary to explore the data (Halliday et al., 2012, Halliday et al., 2013, Minaudo et al., 2015).

In recent years, interpretation of long-term water quality time series has provided useful insight into the water-quality trajectory of major river catchments, such as the Thames (Howden et al., 2010), the Seine (Billen et al., 2007, Romero et al., 2016), the Loire (Minaudo et al., 2015), the Elbe (Lehmann and Rode, 2001) and Baltic rivers (Andersen et al., 2015). Meanwhile, the development of high-frequency sensors has upgraded monitoring resolution to the time scales of fundamental processes, i.e., hourly or sub-hourly time scales. Specifically, these technologies have advanced knowledge of diel cycles produced by stream metabolism, concentration dynamics during storm events and assessment of uncertainty in load estimations (Aubert et al., 2014, Ferrant et al., 2013, Halliday et al., 2013, Pellerin et al., 2009, Rode et al., 2016, Schwientek et al., 2013, Shrestha et al., 2007, Wade et al., 2012). However, combined analysis of long-term and high-frequency water quality time series is rare, because high-frequency sensors are new technologies and are usually not set up near the long-term monitoring stations operated by environmental authorities.

The general objective of the present study was to investigate nitrate-N concentration dynamics in a stream at time scales ranging from 15 min to three decades, with the hypothesis that combining high-frequency and long-term analysis provides a basis to disentangle the factors controlling stream nitrate-N concentrations. Specifically, this study aimed to assess the respective influence of agricultural management and weather and climate variability on observed nitrate-N dynamics to evaluate the effectiveness of mitigation measures aimed at reducing nitrate-N pollution. The selected catchment (Weida, ~ 100 km², eastern Germany) is of particular interest for this purpose because of its management history (as influenced by the reunification of Germany in the early 1990's, an ambitious programme of measures to reduce nitrate-N pollution in the late 1990's, and development of bioenergy crops since the 2000's), and because both high-frequency and long-term monitoring have been performed at the same location.